Approaches for Classifying DNA Variants Found by Sanger Sequencing in a Medical Genetics Laboratory

Abstract

Diagnostic applications of DNA sequencing technologies present a powerful tool for the clinical management of patients. Applications range from better diagnostic classification to identification of therapeutic options, prediction of drug response and toxicity, and carrier testing. Although the advent of massively parallel sequencing technologies has increased the complexity of clinical interpretation of sequence variants by an order of magnitude, the annotation and interpretation of the clinical effects of identified genomic variants remain a challenge regardless of the sequencing technologies used to identify them. Here, we survey methodologies which assist in the diagnostic classification of DNA variants and propose a practical decision analytic protocol to assist in the classification of sequencing variants in a clinical setting. The methods include database queries, software tools for protein consequence, evolutionary conservation and pathogenicity prediction, familial segregation, case–control studies, and literature review. These methods are deliberately pragmatic as diagnostic constraints of clinically useful turnaround times generally preclude obtaining evidence from in vivo or in vitro functional experiments for variant assessment. Clinical considerations require that variant classification is stringent and rigorous, as misinterpretation may lead to inappropriate clinical consequences; thus, multiple parameters and lines of evidence are considered to determine potential biological significance.